Laboratory for Computational Engineering

Computational methods are pervading all branches of science and engineering, helping us to advance our understanding of Nature and foster the development of new technologies. They are also essential for supporting the industry in the process of embracing the ongoing digital transformation, hence, effectively taking advantage of the ever-growing amount of available digital data and computational power.

 

In this context, the Laboratory for Computational Engineering aims at (i) devising novel approaches and algorithms, (ii) employing numerical simulations to understand complex systems and processes, and (iii) solving practically relevant problems to support a sustainable and healthy society.

 

Our focus is on multiscale and data-driven simulations, with the objective to integrate mechanistic modeling, machine learning, and experiments, fusing them into algorithms that interact with the environment (Embodied Machine Learning).

 

The science of porous materials is intrinsically rich in challenging multiscale/multiphysics problems that require cutting-edge computational methods to understand and describe biophysicochemical processes. We are particularly interested in applications that can contribute solutions for carbon negative technologies.

 

The laboratory also has excellent experimental facilities (including two large-scale fluid tunnels and various equipment to investigate processes in porous media), and it is active in advancing electro-optical methods for flow and transport measurements by devising machine learning methods for data analysis and control. For the future, our ambition is to design and test solutions for autonomous experiments.

 

Finally, we are interested in network science for applications to virus transport and epidemiology, power-grid modeling, and other societal dynamics.

https://www.integratedtesting.org/documents/55975/83318/porous_big.jpg/e042877a-8deb-4bdd-881e-0a4438238733?t=1639043344000